The semiconductor industry is continuously moving toward the fabrication of smaller and more complex microelectronic components with higher performance. As a result, many microelectronic components in integrated circuits are becoming smaller and more complex. As the microelectronic components become smaller, the dimensions and/or composition of different features become smaller and have a greater impact on the proper operation of the integrated circuit. These small features should be measured from time to time for various reasons, such as to monitor the fabrication process, to guard against microscopic faults, to understand manufacturing steps or performance levels, etc. However, many microelectronic components of an integrated circuit have several different features. For example, a field effect transistor (FET) includes a source, a drain, a gate, and a gate dielectric. Each feature may vary somewhat in dimension or material property, and a change in any one of these features could impact the electrical performance of the microelectronic component.
Metrology is the science of measurement. One technique used in metrology is scatterometry. In scatterometry techniques, an object is illuminated with electromagnetic radiation, such as light, the light is scattered by the object, and the scattered light is measured at a variety of locations. A model is developed that predicts the intensity and phase change of the scattered light based on various dimensions and properties of the structure, such as the height, width, angle, reflectivity of the material, and composition of the object. The various dimensions and properties of the structure are referred to herein as “parameters.” Various dimensions of the object can then be determined by comparing the actual measured scattered light to the model. However, many different parameters will scatter light, and each variable parameter of the object is represented as an unknown variable in the model. Having more unknown variables in the model increases the complexity of the comparison and reduces the accuracy of the measurement. For example, if the critical dimension is the depth of a valley between two towers, it is difficult to produce an accurate model when other parameters can vary in an unknown manner, such as variations in the distance between the two towers, the shape of the two towers, the composition of the two towers, intersection angles, etc. Measurement accuracy can be improved by using two or more different measurement tools where one or more of the parameters, such as the distance between the towers in the above example, is measured on a different metrology tool and fed forward into the scatterometry model. The scatterometry model will then fix the parameter at the value that was fed in, thereby reducing the number of unknown variables in the model and increasing accuracy. However, each additional measurement step increases the cycle time and manufacturing costs.
Accordingly, it is desirable to provide methods for measuring parameters that utilize a limited number of measurement tools, such as one measurement tool. In addition, it is desirable to provide methods for measuring parameters that utilize existing data without requiring additional measurement steps. Furthermore, other desirable features and characteristics of the various embodiments will become apparent from the subsequent detailed description and the appended claim, taken in conjunction with the accompanying drawings and this background.